SGPB Hambros seeks new ways to talk about risk

By: Caroline Allen | 28 Sep 2012

Introducing a new model for customer dialogue should improve adviser-client discussions on risk and portfolio construction, says SGPB Hambros.

SGPB Hambros has launched a model and process it calls the Dialogue and Asset Allocation Method (D&AA) to enable advisers to have a “better conversation” with wealthy clients about risk and portfolio construction.

Chief investment officer Eric Veleyen (pictured) says the bank had invested heavily in the research behind the two-stage process, comprised of a diagnosis of the portfolio, followed by a review, including simulations of various scenarios, of asset allocation.

“The old approach used to be to show three boxes for risk – high, medium and low, and the client would tick one of them,” Veleyen says. “We saw some clients trying to achieve excessive returns with no risk, and we started to think about a way to help them achieve a more complex understanding.”

Increasing returns

“D&AA allows the client to really understand their portfolios, and for us it is a way to have a better conversation about how to increase returns without increasing risk,” he adds. “If asset allocation is changed abruptly, the client may not achieve their target returns. The model allows us to share figures with customers about the impact of those changes.”

The proprietary process will be offered as part of the management charge to all SGPB Hambros high net worth clients. It has taken eight months and a team of 30 staff to develop the calculation engine, which covers thousands of products globally across nine asset classes: equities, bonds, cash and equivalents, forex, hedge funds, private equity, commodities, real estate and credit.

The client and adviser can add, modify or delete any part of the portfolio and see the effect that change will have over any time period. The model will be based on the portfolio run by SGPB Hambros but can accommodate information about client assets held by other managers and banks.

It also produces a range of best and worst possible outcomes for the portfolio, and can identify the likely scale of risk or loss. “The interesting aspect is that this is not back testing, but forward projection of various scenarios,” notes Verleyen. “It gives the analysis a context and we can then re-shape the portfolio to be more efficient.”